Simultaneous localization and mapping (SLAM) is an active research topic in machine
vision and robotics. It has various applications in many different fields such as mobile robots …

Mobile robots' efficient path planning has long been a challenging task due to the complexity
and dynamism of environments. If an occupancy grid map is used in path planning, the …

A truly autonomous mobile robot have to solve the SLAM problem (ie simultaneous map
building and pose estimation) in order to navigate in an unknown environment …

Simultaneous Localization and Mapping (SLAM) algorithms are crucial for enabling agents
to estimate their position in unknown environments. In autonomous navigation systems …

This article deals with the computational complexity issue of graphbased simultaneous
localization and mapping (SLAM). SLAM allows a robot that is navigating in an unknown …

The real-time capability of multi-camera visual simultaneous localization and mapping
(SLAM) in embedded systems is vital for robotic autonomous navigation. However, owing to …

Graph-based simultaneous localization and mapping (G-SLAM) is an intuitive SLAM
implementation where graphs are used to represent poses, landmarks and sensor …

Simultaneous localization and mapping (SLAM) is a very important application employed in
many realistic scenarios, where a mobile robot builds a map of the environment while also …

In the emerging field of mobile robotics, Simultaneous Localization and Mapping (SLAM) of
robots play an increasingly important role. In spite of the availability of various algorithms …

In the context of the Dismantling and Decommissioning processes, establishing a precise
radiological mapping is essential, as it facilitates the identification of areas with elevated …